Computational imaging without a computer:seeing through random diffusers at the speed of light
作者机构：Electrical and Computer Engineering DepartmentUniversity of CaliforniaLos AngelesLos AngelesCA 90095USA Bioengineering DepartmentUniversity of CaliforniaLos AngelesLos AngelesCA 90095USA California NanoSystems InstituteUniversity of CaliforniaLos AngelesLos AngelesCA 90095USA.
出 版 物：《eLight》 (e光学（英文）)
年 卷 期：2022年第2卷第1期
页 面：42-57页
基 金：The authors acknowledge the U.S.National Science Foundation and Fujikura
主 题：Imaging through diffusers Computational imaging Diffractive neural network Deep learning
摘 要：Imaging through diffusers presents a challenging problem with various digital image reconstruction solutions demonstrated to date using ***,we present a computer-free,all-optical image reconstruction method to see through random diffusers at the speed of *** deep learning,a set of transmissive diffractive surfaces are trained to all-optically reconstruct images of arbitrary objects that are completely covered by unknown,random phase *** the training stage,which is a one-time effort,the resulting diffractive surfaces are fabricated and form a passive optical network that is physically positioned between the unknown object and the image plane to all-optically reconstruct the object pattern through an unknown,new phase *** experimentally demonstrated this concept using coherent THz illumination and all-optically reconstructed objects distorted by unknown,random diffusers,never used during *** digital methods,all-optical diffractive reconstructions do not require power except for the illumination *** diffractive solution to see through diffusers can be extended to other wavelengths,and might fuel various applications in biomedical imaging,astronomy,atmospheric sciences,oceanography,security,robotics,autonomous vehicles,among many others.
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